scholarly journals Performance of the Global Forecast System's medium-range precipitation forecasts in the Niger river basin using multiple satellite-based products

2022 ◽  
Vol 26 (1) ◽  
pp. 167-181
Author(s):  
Haowen Yue ◽  
Mekonnen Gebremichael ◽  
Vahid Nourani
Keyword(s):  
River Basin ◽  
Spatial Scales ◽  
Forecast Accuracy ◽  
Daily Rainfall ◽  
Weather Forecast ◽  
Medium Range ◽  
Climatic Regime ◽  
Niger River ◽  
Sahel Region ◽  
Almost All

Abstract. Accurate weather forecast information has the potential to improve water resources management, energy, and agriculture. This study evaluates the accuracy of medium-range (1–15 d) precipitation forecasts from the Global Forecast System (GFS) over watersheds of eight major dams (Selingue Dam, Markala Dam, Goronyo Dam, Bakolori Dam, Kainji Dam, Jebba Dam, Dadin Kowa Dam, and Lagdo Dam) in the Niger river basin using NASA's Integrated Multi-satellitE Retrievals (IMERG) Final Run merged satellite gauge rainfall observations. The results indicate that the accuracy of GFS forecast varies depending on climatic regime, lead time, accumulation timescale, and spatial scale. The GFS forecast has large overestimation bias in the Guinea region of the basin (wet climatic regime), moderate overestimation bias in the Savannah region (moderately wet climatic regime), but has no bias in the Sahel region (dry climate). Averaging the forecasts at coarser spatial scales leads to increased forecast accuracy. For daily rainfall forecasts, the performance of GFS is very low for almost all watersheds, except for Markala and Kainji dams, both of which have much larger watershed areas compared to the other watersheds. Averaging the forecasts at longer timescales also leads to increased forecast accuracy. The GFS forecasts, at 15 d accumulation timescale, have better performance but tend to overestimate high rain rates. Additionally, the performance assessment of two other satellite products was conducted using IMERG Final estimates as reference. The Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) merged satellite gauge product has similar rainfall characteristics to IMERG Final, indicating the robustness of IMERG Final. The IMERG Early Run satellite-only rainfall product is biased in the dry Sahel region; however, in the wet Guinea and Savannah regions, IMERG Early Run outperforms GFS in terms of bias.

scholarly journals Performance of the Global Forecast System's Medium-Range Precipitation Forecasts in the Niger River Basin

2021 ◽  
Author(s):  
Haowen Yue ◽  
Mekonnen Gebremichael ◽  
Vahid Nourani
Keyword(s):  
River Basin ◽  
Forecast Accuracy ◽  
Weather Forecast ◽  
Heavy Rain ◽  
Annual Rainfall ◽  
Random Errors ◽  
Guinea Coast ◽  
Medium Range ◽  
Niger River ◽  
Rain Rates

Abstract. Weather forecast information has the potential to improve water resources management, energy, and agriculture. This study evaluates the accuracy of medium-range (1–15 day) precipitation forecasts from the Global Forecast System (GFS) over watersheds of eight major dams in the Niger river basin. The Niger basin lies in three latitudinal/climatic sub-regions: Sahel (latitude > 12° N) with annual rainfall of rainfall 400–600 mm, Savannah (latitude 8°–12° N) with annual rainfall of 900–1200 mm, and Guinea Coast (latitude 4°–8° N) with annual rainfall of 1500–2000 mm. The GFS forecast tends to overestimate rainfall in the Guinea Coast and western parts of the Savannah, but estimates well in the Sahel. The overall performance of daily GFS forecast was found to be satisfactory for two watersheds, namely, Kainji (the largest watershed in the basin, predominantly located in the Sahel), and Markala (the second largest watershed, located partly in the Sahel and partly in the Savannah). However, the performance of daily GFS forecast was found to be unsatisfactory in the remaining six watersheds, with GFS forecasts characterized by large random errors, high false alarm, high overestimation bias of low rain rates, and large underestimation bias of heavy rain rates. The GFS forecast accuracy decreases with increasing lead time. The accuracy of GFS forecasts could be improved by applying post-processing techniques involving near-real time satellite rainfall products.

Assessment of Groundwater Geochemistry of Vel River basin, Western Maharashtra, India

2020 ◽  
Vol 4 (1) ◽  
pp. 14-28
Author(s):  
S. K. Gaikwad ◽  
N. D. Pathan ◽  
N. S. Bansode ◽  
S. P. Gaikwad ◽  
Y. P. Badhe ◽  
...  
Keyword(s):  
River Basin ◽  
Anthropogenic Activities ◽  
Geochemical Data ◽  
Total Hardness ◽  
Groundwater Geochemistry ◽  
Average Value ◽  
Rock Water Interaction ◽  
Good For ◽  
Almost All ◽  
Geological Control

To study the chemistry of major ion in groundwater from Vel (Velu) River basin, sixty (60) samples of dug wells and bore wells were collected and analyzed using standard techniques given by APHA. It shows order of dominance for cations, Na+ > Ca2+ > Mg2+ > K+ and in anionic concentration as HCO3- > Cl- > SO42- in groundwater. The pH of groundwater is slightly alkaline (range: pH 7.0 - 8.1), while average values of Electrical Conductivity (EC) is about 2641 µS/cm indicating high mineralization of groundwater. In general, the cationic concentration (Na+, K+, Ca2+ and Mg2+) of the groundwater increase in the downstream side (from Northwest to South east), suggesting geological control on the composition of groundwater while highest concentration is in lower part of the basin are generally associated with the high salinity. In the major anions, bicarbonate (HCO3-) is higher due to rock-water interaction. Average value of chloride is about of 235 mg/L due to discharge zones along with anthropogenic activities. The geochemical data plotted on Piper Trilinear Diagram is showing dominant hydro-chemical facies: Ca2++Mg2+, Na++ K+, Cl-+ SO42- -HCO3- found in 83.3 % samples indicating the alkaline earth exceeding the alkalis and the strong acids exceeds the weak acids. The pH, Total Hardness (TH) and Magnesium (Mg2+) of the samples show more proportion of samples falling above desirable limit. Otherwise the quality of groundwater is good for drinking. The irrigation indices like SAR, KR and SSP were considered to evaluate groundwater suitability for irrigation. Comparing with SAR parameter all samples are excellent to good for irrigation. In SSP, 33.3 % samples are within permissible, while 66.6% samples are doubtful for irrigation purpose. In KR almost all samples (excluding 04 samples in lower side of basin) are suitable for irrigation. So, variations in climate, geology with anthropogenic activities are modifying the groundwater geochemistry of Vel River Basin.

scholarly journals A Comparison between One-Step and Two-Step Nesting Strategy in the Dynamical Downscaling of Regional Climate Model COSMO-CLM at 2.2 km Driven by ERA5 Reanalysis

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 260
Author(s):  
Mario Raffa ◽  
Alfredo Reder ◽  
Marianna Adinolfi ◽  
Paola Mercogliano
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Spatial Scales ◽  
Regional Climate ◽  
Weather Forecast ◽  
Medium Range Weather Forecast ◽  
Spatial And Temporal Scales ◽  
Starting Point ◽  
One Step

Recently, the European Centre for Medium Range Weather Forecast (ECMWF) has released a new generation of reanalysis, acknowledged as ERA5, representing at the present the most plausible picture for the current climate. Although ERA5 enhancements, in some cases, its coarse spatial resolution (~31 km) could still discourage a direct use of precipitation fields. Such a gap could be faced dynamically downscaling ERA5 at convection permitting scale (resolution < 4 km). On this regard, the selection of the most appropriate nesting strategy (direct one-step against nested two-step) represents a pivotal issue for saving time and computational resources. Two questions may be raised within this context: (i) may the dynamical downscaling of ERA5 accurately represents past precipitation patterns? and (ii) at what extent may the direct nesting strategy performances be adequately for this scope? This work addresses these questions evaluating two ERA5-driven experiments at ~2.2 km grid spacing over part of the central Europe, run using the regional climate model COSMO-CLM with different nesting strategies, for the period 2007–2011. Precipitation data are analysed at different temporal and spatial scales with respect to gridded observational datasets (i.e., E-OBS and RADKLIM-RW) and existing reanalysis products (i.e., ERA5-Land and UERRA). The present work demonstrates that the one-step experiment tendentially outperforms the two-step one when there is no spectral nudging, providing results at different spatial and temporal scales in line with the other existing reanalysis products. However, the results can be highly model and event dependent as some different aspects might need to be considered (i.e., the nesting strategies) during the configuration phase of the climate experiments. For this reason, a clear and consolidated recommendation on this topic cannot be stated. Such a level of confidence could be achieved in future works by increasing the number of cities and events analysed. Nevertheless, these promising results represent a starting point for the optimal experimental configuration assessment, in the frame of future climate studies.

Western white pine development in relation to biophysical characteristics across different spatial scales in the Coeur d'Alene River basin in northern Idaho, U.S.A.

2002 ◽  
Vol 32 (7) ◽  
pp. 1109-1125 ◽  
Author(s):  
Theresa B Jain ◽  
Russell T Graham ◽  
Penelope Morgan
Keyword(s):  
River Basin ◽  
Spatial Scales ◽  
Pinus Monticola ◽  
White Pine ◽  
Basal Diameter ◽  
Landscape Characteristics ◽  
Coeur D'alene ◽  
Biophysical Factors ◽  
Western White Pine ◽  
Northern Idaho

Many studies have assessed tree development beneath canopies in forest ecosystems, but results are seldom placed within the context of broad-scale biophysical factors. Mapped landscape characteristics for three watersheds, located within the Coeur d'Alene River basin in northern Idaho, were integrated to create a spatial hierarchy reflecting biophysical factors that influence western white pine (Pinus monticola Dougl. ex D. Don) development under a range of canopy openings. The hierarchy included canopy opening, landtype, geological feature, and weathering. Interactions and individual-scale contributions were identified using stepwise log–linear regression. The resulting models explained 68% of the variation for estimating western white pine basal diameter and 64% for estimating height. Interactions among spatial scales explained up to 13% of this variation and better described vegetation response than any single spatial scale. A hierarchical approach based on biophysical attributes is an excellent method for studying plant and environment interactions.

Identification of Synchronicity in Deterministic Chaotic Attractors for the Downscaling Process in the Bogotá River Basin

2021 ◽  
Author(s):  
Santiago Duarte ◽  
Gerald Corzo ◽  
Germán Santos
Keyword(s):  
Time Series ◽  
Time Delay ◽  
River Basin ◽  
Spatial Scales ◽  
Climatic Variables ◽  
Chaotic Attractors ◽  
Multiple Attractors ◽  
Nearest Neighbours ◽  
Basin Scale ◽  
Non Linear

&lt;p&gt;Bogot&amp;#225;&amp;#8217;s River Basin, it&amp;#8217;s an important basin in Cundinamarca, Colombia&amp;#8217;s central region. Due to the complexity of the dynamical climatic system in tropical regions, can be difficult to predict and use the information of GCMs at the basin scale. This region is especially influenced by ENSO and non-linear climatic oscillation phenomena. Furthermore, considering that climatic processes are essentially non-linear and possibly chaotic, it may reduce the effectiveness of downscaling techniques in this region.&amp;#160;&lt;/p&gt;&lt;p&gt;In this study, we try to apply chaotic downscaling to see if we could identify synchronicity that will allow us to better predict. It was possible to identify clearly the best time aggregation that can capture at the best the maximum relations between the variables at different spatial scales. Aside this research proposes a new combination of multiple attractors. Few analyses have been made to evaluate the existence of synchronicity between two or more attractors. And less analysis has considered the chaotic behaviour in attractors derived from climatic time series at different spatial scales.&amp;#160;&lt;/p&gt;&lt;p&gt;Thus, we evaluate general synchronization between multiple attractors of various climate time series. The Mutual False Nearest Neighbours parameter (MFNN) is used to test the &amp;#8220;Synchronicity Level&amp;#8221; (existence of any type of synchronization) between two different attractors. Two climatic variables were selected for the analysis: Precipitation and Temperature. Likewise, two information sources are used: At the basin scale, local climatic-gauge stations with daily data and at global scale, the output of the MPI-ESM-MR model with a spatial resolution of 1.875&amp;#176;x1.875&amp;#176; for both climatic variables (1850-2005). In the downscaling process, two RCP (Representative Concentration Pathways)&amp;#160; scenarios are used, RCP 4.5 and RCP 8.5.&lt;/p&gt;&lt;p&gt;For the attractor&amp;#8217;s reconstruction, the time-delay is obtained through the&amp;#160; Autocorrelation and the Mutual Information functions. The False Nearest Neighbors method (FNN) allowed finding the embedding dimension to unfold the attractor. This information was used to identify deterministic chaos at different times (e.g. 1, 2, 3 and 5 days) and spatial scales using the Lyapunov exponents. These results were used to test the synchronicity between the various chaotic attractor&amp;#8217;s sets using the MFNN method and time-delay relations. An optimization function was used to find the attractor&amp;#8217;s distance relation that increases the synchronicity between the attractors.&amp;#160; These results provided the potential of synchronicity in chaotic attractors to improve rainfall and temperature downscaling results at aggregated daily-time steps. Knowledge of loss information related to multiple reconstructed attractors can provide a better construction of downscaling models. This is new information for the downscaling process. Furthermore, synchronicity can improve the selection of neighbours for nearest-neighbours methods looking at the behaviour of synchronized attractors. This analysis can also allow the classification of unique patterns and relationships between climatic variables at different temporal and spatial scales.&lt;/p&gt;

COMMERCIAL FAUNA OF WA-TERBODIES IN THE MOSCOW RIVER BASIN IN THE SECOND HALF OF THE 18th CENTURY

2021 ◽  
pp. 94-112
Author(s):  
N. Ozerova
Keyword(s):  
River Basin ◽  
Fish Species ◽  
18Th Century ◽  
Commercial Fish ◽  
Acipenser Ruthenus ◽  
Land Survey ◽  
Ancient Times ◽  
In The Beginning ◽  
Almost All ◽  
Moscow River

Based on the data from economic notes to the General Land Survey, the ranges of commercial fish and crayfish species that inhabited waterbodies of the Moscow River basin in the second half of the 18th century are reconstructed. Eighteen maps showing the distribution of 22 fish species, including Acipenser ruthenus L., Abramis brama L., Barbatula barbatula L., Lota lota L., Sander lucioperca L. and others are compiled. Comparison of commercial fish species that lived in the Moscow River basin in the second half of the 18th century with data from ichthyological studies in the beginning of the XXI century and materials of archaeological surveys shows that almost all of these species have lived in the Moscow River basin since ancient times and have survived to the present day.

scholarly journals Evaluation and Hydrologic Validation of Three Satellite-Based Precipitation Products in the Upper Catchment of the Red River Basin, China

2018 ◽  
Vol 10 (12) ◽  
pp. 1881 ◽  
Author(s):  
Yueyuan Zhang ◽  
Yungang Li ◽  
Xuan Ji ◽  
Xian Luo ◽  
Xue Li
Keyword(s):  
River Basin ◽  
Southwest China ◽  
Spatial Scales ◽  
Red River ◽  
Low Flow ◽  
Efficiency Coefficient ◽  
Monthly Streamflow ◽  
Red River Basin ◽  
Hydrological Applications ◽  
Trmm 3B42

Satellite-based precipitation products (SPPs) provide alternative precipitation estimates that are especially useful for sparsely gauged and ungauged basins. However, high climate variability and extreme topography pose a challenge. In such regions, rigorous validation is necessary when using SPPs for hydrological applications. We evaluated the accuracy of three recent SPPs over the upper catchment of the Red River Basin, which is a mountain gorge region of southwest China that experiences a subtropical monsoon climate. The SPPs included the Tropical Rainfall Measuring Mission (TRMM) 3B42 V7 product, the Climate Prediction Center (CPC) Morphing Algorithm (CMORPH), the Bias-corrected product (CMORPH_CRT), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Climate Data Record (PERSIANN_CDR) products. SPPs were compared with gauge rainfall from 1998 to 2010 at multiple temporal (daily, monthly) and spatial scales (grid, basin). The TRMM 3B42 product showed the best consistency with gauge observations, followed by CMORPH_CRT, and then PERSIANN_CDR. All three SPPs performed poorly when detecting the frequency of non-rain and light rain events (<1 mm); furthermore, they tended to overestimate moderate rainfall (1–25 mm) and underestimate heavy and hard rainfall (>25 mm). GR (Génie Rural) hydrological models were used to evaluate the utility of the three SPPs for daily and monthly streamflow simulation. Under Scenario I (gauge-calibrated parameters), CMORPH_CRT presented the best consistency with observed daily (Nash–Sutcliffe efficiency coefficient, or NSE = 0.73) and monthly (NSE = 0.82) streamflow. Under Scenario II (individual-calibrated parameters), SPP-driven simulations yielded satisfactory performances (NSE >0.63 for daily, NSE >0.79 for monthly); among them, TRMM 3B42 and CMORPH_CRT performed better than PERSIANN_CDR. SPP-forced simulations underestimated high flow (18.1–28.0%) and overestimated low flow (18.9–49.4%). TRMM 3B42 and CMORPH_CRT show potential for use in hydrological applications over poorly gauged and inaccessible transboundary river basins of Southwest China, particularly for monthly time intervals suitable for water resource management.

scholarly journals Analyses of flood peak discharge in Cimadur river basin, Banten Province, Indonesia

2021 ◽  
Vol 331 ◽  
pp. 08006
Author(s):  
Arniza Fitri ◽  
Muhammad Shubhi Nurul Hadie ◽  
Adelia Agustina ◽  
Dian Pratiwi ◽  
Susarman ◽  
...  
Keyword(s):  
River Basin ◽  
Return Period ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Rainfall Distribution ◽  
Flood Peak ◽  
Type Iii ◽  
Pearson Type ◽  
Catchment Areas ◽  
Peak Discharges

Cimadur river basin is one of the most important catchment areas in Lebak District, Banten Province. For the past few years, the catchment has experienced floods during the rainy season. The big issue of flooding has been recorded recently in December 2019 which has caused damage and negative impacts to the local people and surrounding community. This study aims to analyze the possibility of flood peak discharges in the catchment area of the Cimadur river. The flood discharges are calculated for 2, 5, 10, 25, 50, and 100 years return period based on the daily rainfall data from the year 2011 to 2020. The rainfall and land use data are obtained from PT Saeba Consultant. In this study, the hydrological analyses are including 1) analyses of average annual rainfall using the Thiessen method; 2) analyses of rainfall distribution and estimation of design rainfall by considering three methods involving: Log-Normal, Log Pearson Type III, and Gumbel Type 1; and 3) analyses of flood discharges by adopting Nakayasu Synthetic Hydrograph Unit (SHU). The rainfall distribution analyses show that the Log Pearson Type III provided the best fit. Based on the flood peak discharges analyses, the results show that the flood discharges for the 5, 10, 25, and 50 years return period in the Cimadur river basin are 470.71 m3/s, 560.16 m3/s, 698 m3/s, and 820.4 m3/s, respectively.

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